Table 2 Overview of summary measures and dimensions
Dimension of inequality | |||||||
|---|---|---|---|---|---|---|---|
Summary measure | Definition | Formulaa | Economic status | Education | Place of residence | Sex | Subnational region |
Absolute measures | |||||||
Absolute concentration index (ACI) | The ACI is a complex, weighted measure of inequality that indicates the extent to which a health indicator is concentrated among the disadvantaged or advantaged, on an absolute scale. | \( ACI={\displaystyle \sum_j}{p}_j\left(2{X}_j-1\right){y}_j \) | ✓ | ✓ | |||
Between-group variance (BGV) | The BGV is a complex, weighted measure of inequality that shows the squared difference between each subgroup and the national level, on average. The BGV is sensitive to large deviations from the national level (by use of squaring). | \( BGV={\displaystyle \sum_j}{p}_j{\left({y}_j-\mu \right)}^2 \) | ✓ | ||||
Difference (D) | The D is a simple measure of inequality that shows the absolute inequality between two subgroups. | D = y high − y low | ✓ | ✓ | ✓ | ✓ | ✓ |
Mean difference from best performing subgroup (MDB) | The MDB is a complex, weighted measure of inequality that shows the difference between each subgroup and the best performing subgroup, on average. | \( MDB={\displaystyle \sum_j}{p}_j\left|{y}_j-{y}_{ref}\right| \) | ✓ | ||||
Mean difference from mean (MDM) | The MDM is a complex, weighted measure of inequality that shows the absolute difference between each subgroup and the national level, on average. | \( MDM={\displaystyle \sum_j}{p}_j\left|{y}_j-\mu \right| \) | ✓ | ||||
Population attributable risk (PAR) | The PAR is a complex, weighted measure of inequality that shows the potential for improvement in the national level of a health indicator that could be achieved if all subgroups had the same level of health as a reference subgroup. | PAR = y ref − μ | ✓ | ✓ | ✓ | ✓ | ✓ |
Slope index of inequality (SII) | The SII is a complex, weighted measure of inequality that represents the absolute difference in predicted values of a health indicator between the most-advantaged and most-disadvantaged (or vice versa for adverse health outcome indicators), while taking into consideration all the other subgroups – using an appropriate regression model. | SII = v1 − v0 for favourable health intervention indicators; SII = v0 − v1 for adverse health outcome indicators | ✓ | ✓ | |||
Relative measures | |||||||
Index of disparity (IDIS) | The IDIS is a complex measure of inequality that shows the proportional difference between each subgroup and the national level, on average. | \( IDIS=\frac{1}{n}*\frac{{\displaystyle {\sum}_j}\left|{y}_j-\mu \right|}{\mu }*100 \) | ✓ | ||||
Kunst-Mackenbach index (KMI) | The KMI is a complex, weighted measure of inequality that represents the ratio of predicted values of a health indicator of the most-advantaged to the most-disadvantaged (or vice versa for adverse health outcome indicators), while taking into consideration all the other subgroups – using an appropriate regression model. | KMI = v1/v0 for favourable health intervention indicators; KMI = v0/v1 for adverse health outcome indicators | ✓ | ✓ | |||
Mean log deviation (MLD) | The MLD is a complex measure of inequality that takes into account the population share of each subgroup. The MLD is sensitive to large deviations from the national level (by use of logarithm). | \( \mathrm{M}\mathrm{L}\mathrm{D}={\displaystyle \sum_j}{p}_j\left(- \ln \left(\frac{y_j}{\mu}\right)\right)*1000 \) | ✓ | ||||
Population attributable fraction (PAF) | The PAF is a complex, weighted measure of inequality that shows the potential for improvement in the national level of a health indicator, in relative terms, that could be achieved if all subgroups had the same level of health as a reference subgroup. | \( PAF=\frac{PAR}{\mu }*100 \) | ✓ | ✓ | ✓ | ✓ | ✓ |
Ratio (R) | The R is a simple measure of inequality that shows the relative inequality between two subgroups. | R = y high /y low | ✓ | ✓ | ✓ | ✓ | ✓ |
Relative concentration index (RCI) | The RCI is a complex, weighted measure of inequality that indicates the extent to which a health indicator is concentrated among the disadvantaged or the advantaged, on a relative scale. | \( RCI=\frac{ACI}{\mu }*100 \) | ✓ | ✓ | |||
Relative index of inequality (RII) | The RII is a complex, weighted measure of inequality that represents the relative difference (proportional to the national level) in predicted values of health indicator between the most-advantaged and most-disadvantaged, while taking into consideration all the other subgroups – using an appropriate regression model. | \( RII=\frac{SII}{\mu } \) | ✓ | ✓ | |||
Theil index (TI) | The TI is a complex measure of inequality, that takes into account the population share of each subgroup. The TI is sensitive to large deviations from the national level (by use of logarithm). | \( TI={\displaystyle \sum_j}{p}_j\frac{y_j}{\mu } \ln \frac{y_j}{\mu }*1000 \) | ✓ | ||||